SCIENTIFIC COMPUTING AND IMAGING INSTITUTE
at the University of Utah

I have an interdisciplinary background in engineering (mechanical, aerospace, and software). I am broadly interested in using computing tools and techniques to understand and solve complex interdisciplinary problems related to natural phenomena and engineered systems.

My current academic interests revolve around theory, implementation, and applications of Material Point Method (MPM). MPM is a very powerful mathematical technique for accurately simulating the real-world behavior of materials (solids, liquids, and gases).

I'm currently developing a high-performance computing asynchronous-execution task-based simulation capability for modeling additive manufacturing (laser sintering) using material point method (MPM) - with a specific emphasis on simulating features like phase change, laser heating models, and energy modeling. MPM at scale is computationally very expensive, so the goal is to extend Uintah MPM code to application specific needs and implementing them with GPU-based parallel architectures.

For non-computational science readers: it basically says that I am working on simulating a manufacturing process using a clever mathematical technique on very powerful computers to get results as fast as possible and verify them against real-world measurements and data. Why? Every man-made product (ranging everything from a car to an iPhone) involves manufacturing components at some point. Fabricating complex three-dimensional products is an inefficient process; traditional manufacturing methods are fast, scalable but are highly wasteful. To improve quality, speed, efficiency, and durability of additive manufacturing requires accurate physical and computational models. Exploring the barriers by solving one small problem at a time.